Thank you for the compliment! My code runs in a Windows environment using a GPU 3050 for training. First, I created a virtual environment using Anaconda, and then I installed the following necessary libraries via pip:
torch 2.4.1
scikit-learn 1.5.2
matplotlib 3.9.2
Next, you need to download the RML2016.10a dataset and place it in the RML directory. You can use some functions in data_processor.py to view the data, and then run the train.py file to start the training. Make sure to modify the training parameters in the parser to fit your needs. After training, you'll get a saved JSON file, and you can visualize the results again using functions from data_processor.py.
If you have any other questions, feel free to ask!
Thank you for the compliment! My code runs in a Windows environment using a GPU 3050 for training. First, I created a virtual environment using Anaconda, and then I installed the following necessary libraries via pip:
torch 2.4.1 scikit-learn 1.5.2 matplotlib 3.9.2
Next, you need to download the RML2016.10a dataset and place it in the RML directory. You can use some functions in data_processor.py to view the data, and then run the train.py file to start the training. Make sure to modify the training parameters in the parser to fit your needs. After training, you'll get a saved JSON file, and you can visualize the results again using functions from data_processor.py.
If you have any other questions, feel free to ask!